This invention relates to an auto setup process for automatically setting gradation, exposure and other conditions for image processing. More specifically, the invention relates to an auto setup process which executes the auto setup of a captured image photoelectrically read out, in particular a prescanned image roughly captured, by performing auto setup operations to determine an image transforming mapping such as a transformation function, a look-up table (LUT) or a transformation matrix.
In a conventional image forming apparatus such as a photographic printer, a copier, a proof printer and a platemaking apparatus, the image on a transmission original (e.g. a negative film or a reversal film) or a reflection original is projected directly onto an output medium, say, a light-sensitive material (this step is called "areal exposure") and subsequently developed to reproduce a photographic image, a copy image, a proof (pre-proof) or a press plate. Prior to exposure, the original image is photoelectrically and roughly captured with an image sensor such as a CCD, and the gradation and exposure conditions that match the output medium are determined on the basis of the roughly captured image which is commonly called a "prescanned image". However, the conventional image forming apparatus which perform areal exposure has only a limited set of parameters that can be adjusted in compliance with the determined exposure conditions. The adjustment is also limited because it must be performed evenly for all areas of the original image. Hence, it is extremely difficult to accomplish the proper adjustment for the whole part of the original image.
A technology that has recently become possible to implement with the above-described image forming apparatus is as follows. An original image is captured photoelectrically with an image reader such as a scanner having a solid-state imaging device such as a CCD so that it is converted to digital image signal. These digital image signals are then subjected to various image processing steps so as to create image data that are optimal for recording on a light-sensitive material. Using a light beam, say, a laser beam modulated in accordance with the resulting image data, the light-sensitive material is scan exposed to record the original image as a latent image. This latent image in turn, is then developed and otherwise processed to give a reproduced image.
In an image forming apparatus capable of such "digital processing" of image signals, the gradation and exposure conditions of the captured image can be adjusted on a pixel basis for the whole or part of the original image or for individual. Hence, the proper adjustment can be accomplished as finely as possible for the entire part of the original image.
The image forming apparatus that performs such "digital processing" is also adapted to effect an auto setup procedure for determining gradation, exposure and other image processing conditions under which the original image captured with an image reader such as a scanner, can be reproduced optimally on an output medium in spite of the variations in gradation, exposure and other conditions for the processing of the input image (to be captured). To this end, the required image processing conditions are automatically set from the captured image, particularly a prescanned image, as a mapping such as a transformation function, LUT or a transformation matrix. Using the thus set mapping, image data finely captured for exposure purposes. Namely, finely scanned image data, are transformed into image processed data, commonly called "as-auto setup image data".
To automatically determine the mapping such as a transformation function, LUT or a transformation matrix that transform the finely scanned image data on the basis of the prescanned image data, auto setup operations are performed. Two typical examples of such operations are as follows: one is a histogram process in which density histograms are constructed from the prescanned image data and the densities of highlights and shadows are set automatically. The other is regional processing in which the original image is split into regions and searched through the regions using the prescanned image data and quantitative image features such as representative or average values for the split regions or the whole original image, for example, LATD (large area transmittance density) are extracted, or a region having a specified quantitative image feature is searched through and extracted.
Further, referring to the auto setup operations, the image resolution suitable for processing differs from one process to another, particularly between the histogram process and the regional processing. In the histogram process which is often employed to determine the densities of highlights and shadows, an image of the highest possible resolution or an image subjected to minimal processing, for example, an image that has not been subjected to noise reduction (which, in the absence of limitations on the image memory's capacity and the processing time, is an image that is the closest possible to a finely-scanned image) is desired. On the other hand, in the regional processing which often involves determination of the representative or average values of regions or searching through a region having a specified feature value, there is a need to prevent the offsets that may occur in the representative or average values of regions or in the extraction of a region having a specified feature value on account of the noise in the image data and, in addition, the processing takes time to perform. Therefore, a noise-reduced image or an image of a medium or a low resolution, particularly one that has been reduced in resolution by noise reduction, is desirable.
However, in the auto setup operations described above, the histogram process, the regional processing and other processing are conventionally performed on the same prescanned image, namely, the prescanned image having the same resolution. Therefore, if a prescanned image of high resolution is employed with a view to performing the correct histogram process, an image memory of large capacity is required but then the overall cost and processing time are increased. In addition, the noise in the image data is not reduced by a sufficient amount to accomplish the correct regional processing. Conversely, if a noise-reduced prescanned image of a medium or a low resolution is employed in order to perform the correct regional processing, the intended regional processing can be accomplished with high efficiency. However other hand, the densities of highlights will decrease and those of shadows will increase in the histogram process, making it impossible to achieve the correct representation of gradations.